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Want to Work at One of the Top Companies in America? Focus on This Skillset

May 24, 2017

In 2012, the Harvard Business Review declared data scientists as the “sexiest” job of the 21st century, meaning data scientists are the most sought-after professionals on the market.

Well, there’s a lot of truth to that. We at LinkedIn analyzed the skills the top companies in America are looking for. Eighteen of the top 20 – 90 percent! – of the skills top companies are looking for the most directly relate to data science.

Specifically, we looked at what skills correlated to the most InMails from recruiters at America's top 50 companies. From that, we came up with a list of the 20 most in-demand skills – top of the list was Voldemort, a distributed data store commonly used by data scientists.

The trend continued. Nearly all of the 20 skills at America’s top companies are searching for the most are skills needed to perform data science.

A bit of background

Recently, LinkedIn released the Top Companies list, which highlights the most sought-after companies by professionals (you can read the full methodology here). The list included a wide range of companies, from Google to Under Armour to the Walt Disney Company.

From that list, we looked at the skills recruiters at those companies were searching for. To determine that, we looked at InMails – messages that recruiters at those companies send out to members on LinkedIn.

We then found the skills individuals have on their profile that correlate with the InMail traffic they get. And we defined "desirable" skills as ones that elicit the most InMails per member.

Using that formula, we came up with a list of the 20 most desired skills at the top 50 companies in America. Here’s the list:

Voldemort

Cascalog

Cascading

BigTable

Avro

Relevance

Stream Processing

Source Depot

Accumulo

Scalability

Membase

MapReduce

Large Scale Systems

Collaborative Filtering

Thrift

Distributed Storage

Concurrency

Apache Storm

Guice

Apache Mesos

Eighteen of those 20 skills are at least partially related to data science. The only two exceptions are Source Deport (#8) and Guice (#19), which are more related to development.

Why data science is at such a premium

Here’s the real question: why is data science so important?

A big part is the amount of data companies are now collecting. IBM reports that we create 2.5 quintillion bytes of data each day, and more than 90 percent of the world’s data has been created in the past two years.

All of this data represents a huge advantage to companies – potentially. Just look at it from a marketing lens: using data, you can theoretically determine who is most likely to buy, when they are most likely to buy and the biggest barrier to purchase, among a thousand other possibilities.

The challenge is figuring out how to ask the right questions and how to ensure the data is accurate. Data scientists are at the front lines of that battle: their job is to determine the right questions to ask, and to ask them in the right way, so that data can be used in the best way possible.

Additionally, data scientists are creating the models needed for machine learning and artificial intelligence. The key to this AI having value is smart data scientists, who create the right algorithms for it to follow.

Bottom line, it’s been said that the biggest asset for companies like Google, Amazon, even Walt Disney, isn’t the products they produce but the data they collect. But all of that data is useless, unless you have people who know how to use it best.

And that’s exactly why data scientists are so critical today. There’s a lot of data out there, but few people who know how to best use that data. Hence, if you can learn those skills, you make yourself very desirable to the top companies in the United States.